Ensemble prediction-based dynamic robust multi-objective optimization methods
Many real-world multi-objective optimization problems are subject to environmental changes over time, resulting in changing Pareto-optima. Wide studies on solving dynamic multi-objective optimization problems have so far concentrated on tracking moving Pareto-optima as soon as possible. In practice,...
Uloženo v:
| Vydáno v: | Swarm and evolutionary computation Ročník 48; s. 156 - 171 |
|---|---|
| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier B.V
01.08.2019
|
| Témata: | |
| ISSN: | 2210-6502 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | Many real-world multi-objective optimization problems are subject to environmental changes over time, resulting in changing Pareto-optima. Wide studies on solving dynamic multi-objective optimization problems have so far concentrated on tracking moving Pareto-optima as soon as possible. In practice, however, a new solution every time the environmental change may be different from the previous optima, causing the expensive switching-cost. To this end, dynamic robust multi-objective optimization method is developed to find robust Pareto-optima over time whose performance is acceptable for the current and subsequently changed environments. With the purpose of measuring the robustness of a candidate, its fitness values in the subsequent environments are estimated by ensemble prediction methods constructed by moving average(MA), autoregressive(AR), and single exponential smoothing(SES). MA-, SES- and AR-based sub-prediction models are synthesized by the weight sum. The weights can be the pre-set constant or the binary/real number adjusted in terms of the prediction error. To examine the performance of the developed algorithm, the proposed prediction strategies are compared with three single prediction methods for 11 dynamic benchmark functions. The experimental results indicate that ensemble prediction methods have the better robustness than the single prediction models and can effectively tackle dynamic robust multi-objective optimization problems. |
|---|---|
| AbstractList | Many real-world multi-objective optimization problems are subject to environmental changes over time, resulting in changing Pareto-optima. Wide studies on solving dynamic multi-objective optimization problems have so far concentrated on tracking moving Pareto-optima as soon as possible. In practice, however, a new solution every time the environmental change may be different from the previous optima, causing the expensive switching-cost. To this end, dynamic robust multi-objective optimization method is developed to find robust Pareto-optima over time whose performance is acceptable for the current and subsequently changed environments. With the purpose of measuring the robustness of a candidate, its fitness values in the subsequent environments are estimated by ensemble prediction methods constructed by moving average(MA), autoregressive(AR), and single exponential smoothing(SES). MA-, SES- and AR-based sub-prediction models are synthesized by the weight sum. The weights can be the pre-set constant or the binary/real number adjusted in terms of the prediction error. To examine the performance of the developed algorithm, the proposed prediction strategies are compared with three single prediction methods for 11 dynamic benchmark functions. The experimental results indicate that ensemble prediction methods have the better robustness than the single prediction models and can effectively tackle dynamic robust multi-objective optimization problems. |
| Author | Guo, Yinan Yang, Huan Chen, Meirong Gong, Dunwei Cheng, Jian |
| Author_xml | – sequence: 1 givenname: Yinan surname: Guo fullname: Guo, Yinan organization: School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, China – sequence: 2 givenname: Huan surname: Yang fullname: Yang, Huan organization: School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, China – sequence: 3 givenname: Meirong surname: Chen fullname: Chen, Meirong email: cmrzl@cumt.edu.cn organization: School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, China – sequence: 4 givenname: Jian surname: Cheng fullname: Cheng, Jian organization: School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, China – sequence: 5 givenname: Dunwei surname: Gong fullname: Gong, Dunwei organization: School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, China |
| BookMark | eNqFkLtOAzEQRV0EiRDyBTT7A7t47H0WFCgKDymIBmrLj1nh1e46sp2g8PVsEioKmGaaOaN7zxWZjW5EQm6AZkChvO2y8Il7lzEKTUZ5RqGYkTljQNOyoOySLEPo6DQlZUXRzMnLegw4qB6TrUdjdbRuTJUMaBJzGOVgdeKd2oWYDLs-2tSpDqejPSZuG-1gv-SRSAaMH86Ea3LRyj7g8mcvyPvD-m31lG5eH59X95tUc8pjKk1RKGggR6ibXLZQ6VzxWrMaSkDFQRUtlRVrqGwU43VlSgM5l6VRKpem5QvSnP9q70Lw2Apt4ylJ9NL2Aqg46hCdOOkQRx2CcjHpmFj-i916O0h_-Ie6O1M41dpb9CJoi6OenPlJiDDO_sl_Axq2gQo |
| CitedBy_id | crossref_primary_10_1016_j_asoc_2020_107027 crossref_primary_10_1016_j_asoc_2020_106733 crossref_primary_10_1016_j_swevo_2020_100829 crossref_primary_10_3390_math9040420 crossref_primary_10_1007_s10489_020_01861_7 crossref_primary_10_1007_s00521_022_07023_9 crossref_primary_10_1016_j_eswa_2021_116126 crossref_primary_10_1016_j_artmed_2021_102228 crossref_primary_10_1109_TEVC_2022_3222844 crossref_primary_10_1007_s10489_022_03934_1 crossref_primary_10_1016_j_swevo_2020_100667 crossref_primary_10_1109_TCYB_2022_3159584 crossref_primary_10_1016_j_ins_2022_01_008 crossref_primary_10_1016_j_asoc_2021_107838 crossref_primary_10_1109_TNNLS_2024_3397393 crossref_primary_10_1016_j_compbiomed_2022_105536 crossref_primary_10_1186_s12859_022_05091_1 crossref_primary_10_1016_j_swevo_2023_101409 crossref_primary_10_1016_j_asoc_2021_108094 crossref_primary_10_1016_j_swevo_2024_101621 crossref_primary_10_1109_TEVC_2023_3306017 crossref_primary_10_1109_TEVC_2019_2925358 crossref_primary_10_21303_2504_5695_2025_003762 crossref_primary_10_3390_math10193466 crossref_primary_10_1016_j_swevo_2020_100806 crossref_primary_10_1145_3524495 crossref_primary_10_1016_j_cie_2021_107523 crossref_primary_10_1007_s00521_020_05000_8 crossref_primary_10_1016_j_eswa_2022_118088 crossref_primary_10_1080_08839514_2023_2222257 crossref_primary_10_1109_TEVC_2023_3250350 crossref_primary_10_1186_s12873_023_00824_8 crossref_primary_10_1016_j_knosys_2020_105518 crossref_primary_10_1007_s00500_019_04365_w crossref_primary_10_1109_TCSS_2023_3293331 crossref_primary_10_1016_j_asoc_2020_106160 crossref_primary_10_1109_TASE_2020_3011428 crossref_primary_10_1109_TETCI_2023_3251400 crossref_primary_10_1016_j_asoc_2021_107258 crossref_primary_10_1007_s40789_022_00516_x crossref_primary_10_1016_j_swevo_2024_101693 crossref_primary_10_1016_j_ins_2023_03_111 crossref_primary_10_1002_aisy_202500172 crossref_primary_10_1016_j_engappai_2023_105944 crossref_primary_10_1109_TEVC_2023_3235196 crossref_primary_10_1109_TEVC_2023_3313689 crossref_primary_10_1016_j_asoc_2022_108493 crossref_primary_10_1016_j_asoc_2022_109622 crossref_primary_10_1016_j_swevo_2024_101566 crossref_primary_10_1016_j_swevo_2023_101420 crossref_primary_10_1016_j_ins_2024_120999 crossref_primary_10_1038_s41598_021_95159_4 crossref_primary_10_1016_j_ins_2022_05_050 crossref_primary_10_1109_TEVC_2019_2951217 crossref_primary_10_1007_s40747_022_00889_1 crossref_primary_10_1016_j_eswa_2021_115620 crossref_primary_10_1016_j_future_2020_01_048 crossref_primary_10_1016_j_ins_2022_04_002 crossref_primary_10_1016_j_eswa_2022_116725 crossref_primary_10_1016_j_asoc_2020_106764 crossref_primary_10_1016_j_asoc_2022_109915 crossref_primary_10_1016_j_knosys_2021_107215 crossref_primary_10_1109_TCYB_2022_3174519 crossref_primary_10_1007_s40747_024_01656_0 crossref_primary_10_1016_j_knosys_2022_108640 crossref_primary_10_1007_s40747_022_00824_4 crossref_primary_10_1109_ACCESS_2020_3031498 crossref_primary_10_1109_TEVC_2022_3180590 crossref_primary_10_1016_j_swevo_2021_100872 crossref_primary_10_1016_j_knosys_2021_107224 crossref_primary_10_1155_2022_9924163 crossref_primary_10_1109_ACCESS_2020_2990500 crossref_primary_10_1155_2022_4418706 crossref_primary_10_1016_j_swevo_2023_101461 crossref_primary_10_1007_s40747_020_00232_6 crossref_primary_10_1016_j_ins_2021_03_066 crossref_primary_10_3390_min13030431 crossref_primary_10_1016_j_swevo_2021_100849 crossref_primary_10_1109_TETCI_2021_3079966 crossref_primary_10_1109_ACCESS_2020_2972631 crossref_primary_10_1038_s41598_023_41855_2 crossref_primary_10_1155_2019_8405961 crossref_primary_10_1016_j_asoc_2020_106641 crossref_primary_10_1038_s41598_021_99617_x crossref_primary_10_1109_TFUZZ_2020_2979119 crossref_primary_10_1016_j_ins_2021_05_064 crossref_primary_10_3390_electronics12224609 crossref_primary_10_1016_j_knosys_2022_108343 crossref_primary_10_1016_j_jclepro_2021_126066 crossref_primary_10_1016_j_ijpe_2021_108315 crossref_primary_10_1016_j_swevo_2020_100795 crossref_primary_10_1016_j_swevo_2021_100974 crossref_primary_10_3390_pr12010189 crossref_primary_10_1016_j_asoc_2019_105981 crossref_primary_10_1016_j_swevo_2021_100975 crossref_primary_10_1016_j_asoc_2019_105988 crossref_primary_10_1016_j_eswa_2025_129304 crossref_primary_10_1016_j_apenergy_2023_120879 crossref_primary_10_1016_j_asoc_2022_108694 crossref_primary_10_1109_ACCESS_2021_3096877 crossref_primary_10_1109_TETCI_2021_3067104 |
| Cites_doi | 10.1016/j.asoc.2007.07.005 10.1109/TEVC.2003.810758 10.1109/TEVC.2008.925798 10.1109/TEVC.2013.2281535 10.1016/j.swevo.2016.12.005 10.1109/TEVC.2008.920671 10.1109/TEVC.2005.846356 10.1016/j.ins.2014.02.123 10.1016/j.swevo.2012.05.001 10.1109/TEVC.2007.892759 10.1007/s12293-012-0090-2 10.1109/TCBB.2017.2652453 10.1109/TEVC.2017.2669638 10.1109/TCYB.2016.2602561 10.1007/s12293-009-0026-7 10.1038/s41598-017-00416-0 10.1109/TEVC.2011.2180533 10.1109/TCYB.2013.2245892 10.1016/j.procs.2013.10.028 10.1016/j.swevo.2013.08.004 10.1109/TCBB.2017.2685320 10.1016/j.ejor.2017.03.048 10.1007/s00521-016-2572-5 10.1016/j.asoc.2017.08.004 10.1016/j.ins.2017.02.029 10.1109/MCI.2015.2471235 10.1109/TEVC.2004.831456 10.1016/j.swevo.2018.03.010 10.1109/TCYB.2014.2304475 10.1016/j.asoc.2017.05.008 10.1109/TEVC.2004.826067 10.1007/s00500-014-1477-4 |
| ContentType | Journal Article |
| Copyright | 2019 Elsevier B.V. |
| Copyright_xml | – notice: 2019 Elsevier B.V. |
| DBID | AAYXX CITATION |
| DOI | 10.1016/j.swevo.2019.03.015 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| EndPage | 171 |
| ExternalDocumentID | 10_1016_j_swevo_2019_03_015 S2210650218302712 |
| GroupedDBID | --K --M .~1 0R~ 1~. 1~5 4.4 457 4G. 5VS 7-5 8P~ AAAKF AABVA AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AARIN AATLK AAXUO AAYFN ABAOU ABBOA ABGRD ABMAC ABUCO ABXDB ABYKQ ACAZW ACDAQ ACGFS ACNNM ACRLP ACZNC ADBBV ADEZE ADMUD ADQTV ADTZH AEBSH AECPX AEKER AENEX AEQOU AFKWA AFTJW AFXIZ AGHFR AGUBO AGYEJ AHJVU AHZHX AIALX AIEXJ AIKHN AITUG AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD APLSM ARUGR AXJTR BJAXD BKOJK BLXMC CBWCG EBS EFJIC EFLBG EJD FDB FEDTE FIRID FNPLU FYGXN GBLVA GBOLZ HAMUX HVGLF HZ~ J1W JJJVA KOM M41 MHUIS MO0 N9A O-L O9- OAUVE P-8 P-9 PC. Q38 RIG ROL SDF SES SPC SPCBC SSA SSB SSD SST SSV SSW SSZ T5K ~G- AATTM AAXKI AAYWO AAYXX ABJNI ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO AEIPS AEUPX AFJKZ AFPUW AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP CITATION EFKBS ~HD |
| ID | FETCH-LOGICAL-c303t-ad55b1914e1894af17c4b38c28161eb31b5f0a7290a9b2387d6d143a6dbb4adf3 |
| ISICitedReferencesCount | 111 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000473374800011&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 2210-6502 |
| IngestDate | Tue Nov 18 21:01:06 EST 2025 Sat Nov 29 05:44:58 EST 2025 Fri Feb 23 02:26:28 EST 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Dynamic multi-objective optimization problem Ensemble prediction Robust Pareto-optimum over time Evolutionary algorithm |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c303t-ad55b1914e1894af17c4b38c28161eb31b5f0a7290a9b2387d6d143a6dbb4adf3 |
| PageCount | 16 |
| ParticipantIDs | crossref_citationtrail_10_1016_j_swevo_2019_03_015 crossref_primary_10_1016_j_swevo_2019_03_015 elsevier_sciencedirect_doi_10_1016_j_swevo_2019_03_015 |
| PublicationCentury | 2000 |
| PublicationDate | August 2019 2019-08-00 |
| PublicationDateYYYYMMDD | 2019-08-01 |
| PublicationDate_xml | – month: 08 year: 2019 text: August 2019 |
| PublicationDecade | 2010 |
| PublicationTitle | Swarm and evolutionary computation |
| PublicationYear | 2019 |
| Publisher | Elsevier B.V |
| Publisher_xml | – name: Elsevier B.V |
| References | Ruan, Yu, Zheng (bib15) 2017; 58 Jin, Branke (bib26) 2005; 9 Deb, Jain (bib47) 2014; 18 Xu, Zhang, Gong (bib6) 2018; 15 Gee, Tan, Alippi (bib24) 2017; 47 Guo, Ji, Ji (bib9) 2018 Goh, Tan (bib50) 2009 Yu, Jin, Tang (bib32) 2010 Helbig, Engelbrecht (bib8) 2014; 14 Nguyen, Yang, Branke (bib1) 2012; 6 Hatzakis, Wallace (bib37) 2006 Kundu, Biswas, Das (bib19) 2013 Zou, Li, Yang (bib20) 2019; 44 Farina, Deb, Amato (bib11) 2004; 8 Chen, Guo, Liu (bib36) 2015; 2015 Muruganantham, Zhao, Gee (bib38) 2013; 24 Guo, Chen, Fu (bib33) 2014 Coello, Pulido, Lechuga (bib45) 2004; 8 Zou, Li, Yang (bib13) 2017; 61 Salomon, Avigad, Fleming (bib17) 2014; 44 Wang, Tan (bib40) 2017 Koo, Goh, Tan (bib28) 2010; 2 Xu (bib43) 2005 Chen, Guo, Gong, Yang (bib44) 2017; 43 Guo, Zhang, Cheng (bib10) 2018; 30 Jin, Tang, Yu (bib34) 2013; 5 Zhang (bib2) 2008; 8 Fu, Sendhoff, Tang (bib35) 2013 Wu, Jin, Liu (bib30) 2015; 19 Zitzler, Thiele, Laumanns (bib52) 2003; 7 Zhou, Jin, Zhang (bib29) 2014; 44 Mavrovouniotis, Li, Yang (bib3) 2017; 33 Chen, Li, Yao (bib25) 2018; 22 Zhang, Gong, Sun, Guo (bib53) 2017 March 23; 7 Huang, Ding, Hao (bib31) 2017; 394 Guo, Cheng, Luo (bib4) 2018; 15 Mavrovouniotis, Li, Yang (bib21) 2017; 33 Liu, Zeng (bib27) 2013; 24 Zhang, Li (bib48) 2007; 11 Deb, Karthik (bib16) 2007 Yang (bib5) 2015 Nguyen, Yao (bib7) 2012; 16 Zitzler, Laumanns, Thiele (bib46) 2001 Nguyen, Yang, Branke (bib18) 2012; 6 Greeff, Engelbrecht (bib12) 2010 Raquel, Yao (bib22) 2013 Goh, Tan (bib23) 2009; 13 Wang, Guo, Gandomi (bib41) 2014; 274 Ren, Zhang, Suganthan (bib39) 2016; 11 Box, Jenkins, Reinsel (bib42) 1994 Li, Zhang (bib49) 2009; 13 Liu, Li, Mu (bib14) 2017; 261 Biswas, Das, Suganthan (bib51) 2014 Zitzler (10.1016/j.swevo.2019.03.015_bib46) 2001 Chen (10.1016/j.swevo.2019.03.015_bib25) 2018; 22 Yang (10.1016/j.swevo.2019.03.015_bib5) 2015 Deb (10.1016/j.swevo.2019.03.015_bib16) 2007 Zhou (10.1016/j.swevo.2019.03.015_bib29) 2014; 44 Ren (10.1016/j.swevo.2019.03.015_bib39) 2016; 11 Zhang (10.1016/j.swevo.2019.03.015_bib2) 2008; 8 Wu (10.1016/j.swevo.2019.03.015_bib30) 2015; 19 Greeff (10.1016/j.swevo.2019.03.015_bib12) 2010 Koo (10.1016/j.swevo.2019.03.015_bib28) 2010; 2 Jin (10.1016/j.swevo.2019.03.015_bib34) 2013; 5 Goh (10.1016/j.swevo.2019.03.015_bib23) 2009; 13 Guo (10.1016/j.swevo.2019.03.015_bib4) 2018; 15 Kundu (10.1016/j.swevo.2019.03.015_bib19) 2013 Zou (10.1016/j.swevo.2019.03.015_bib20) 2019; 44 Yu (10.1016/j.swevo.2019.03.015_bib32) 2010 Wang (10.1016/j.swevo.2019.03.015_bib40) 2017 Guo (10.1016/j.swevo.2019.03.015_bib10) 2018; 30 Raquel (10.1016/j.swevo.2019.03.015_bib22) 2013 Deb (10.1016/j.swevo.2019.03.015_bib47) 2014; 18 Zhang (10.1016/j.swevo.2019.03.015_bib53) 2017; 7 Nguyen (10.1016/j.swevo.2019.03.015_bib18) 2012; 6 Liu (10.1016/j.swevo.2019.03.015_bib14) 2017; 261 Huang (10.1016/j.swevo.2019.03.015_bib31) 2017; 394 Goh (10.1016/j.swevo.2019.03.015_bib50) 2009 Zou (10.1016/j.swevo.2019.03.015_bib13) 2017; 61 Li (10.1016/j.swevo.2019.03.015_bib49) 2009; 13 Jin (10.1016/j.swevo.2019.03.015_bib26) 2005; 9 Nguyen (10.1016/j.swevo.2019.03.015_bib7) 2012; 16 Chen (10.1016/j.swevo.2019.03.015_bib36) 2015; 2015 Nguyen (10.1016/j.swevo.2019.03.015_bib1) 2012; 6 Xu (10.1016/j.swevo.2019.03.015_bib6) 2018; 15 Zhang (10.1016/j.swevo.2019.03.015_bib48) 2007; 11 Wang (10.1016/j.swevo.2019.03.015_bib41) 2014; 274 Muruganantham (10.1016/j.swevo.2019.03.015_bib38) 2013; 24 Biswas (10.1016/j.swevo.2019.03.015_bib51) 2014 Helbig (10.1016/j.swevo.2019.03.015_bib8) 2014; 14 Hatzakis (10.1016/j.swevo.2019.03.015_bib37) 2006 Farina (10.1016/j.swevo.2019.03.015_bib11) 2004; 8 Zitzler (10.1016/j.swevo.2019.03.015_bib52) 2003; 7 Mavrovouniotis (10.1016/j.swevo.2019.03.015_bib21) 2017; 33 Ruan (10.1016/j.swevo.2019.03.015_bib15) 2017; 58 Salomon (10.1016/j.swevo.2019.03.015_bib17) 2014; 44 Gee (10.1016/j.swevo.2019.03.015_bib24) 2017; 47 Box (10.1016/j.swevo.2019.03.015_bib42) 1994 Liu (10.1016/j.swevo.2019.03.015_bib27) 2013; 24 Mavrovouniotis (10.1016/j.swevo.2019.03.015_bib3) 2017; 33 Coello (10.1016/j.swevo.2019.03.015_bib45) 2004; 8 Guo (10.1016/j.swevo.2019.03.015_bib33) 2014 Xu (10.1016/j.swevo.2019.03.015_bib43) 2005 Fu (10.1016/j.swevo.2019.03.015_bib35) 2013 Guo (10.1016/j.swevo.2019.03.015_bib9) 2018 Chen (10.1016/j.swevo.2019.03.015_bib44) 2017; 43 |
| References_xml | – year: 1994 ident: bib42 article-title: Time Series Analysis: Forecasting and Control – volume: 6 start-page: 1 year: 2012 end-page: 24 ident: bib1 article-title: Evolutionary dynamic optimization: a survey of the state of the art publication-title: Swarm Evol. Comput. – volume: 6 start-page: 1 year: 2012 end-page: 24 ident: bib18 article-title: Evolutionary dynamic optimization: a survey of the state of the art publication-title: Swarm Evol. Comput. – start-page: 3192 year: 2014 end-page: 3199 ident: bib51 article-title: Evolutionary multiobjective optimization in dynamic environments: a set of novel benchmark functions publication-title: 2014 IEEE Congress on Evolutionary Computation (CEC) – volume: 274 start-page: 17 year: 2014 end-page: 34 ident: bib41 article-title: Chaotic krill herd algorithm publication-title: Inf. Sci. – volume: 44 start-page: 2221 year: 2014 end-page: 2231 ident: bib17 article-title: Active robust optimization: enhancing robustness to uncertain environments publication-title: IEEE Trans. Cybern. – start-page: 629 year: 2015 end-page: 649 ident: bib5 article-title: Evolutionary computation for dynamic optimization problems publication-title: Proceedings of the 2015th Conference on Genetic and Evolutionary Computation – volume: 394 start-page: 183 year: 2017 end-page: 197 ident: bib31 article-title: A multi-objective approach to robust optimization over time considering switching cost publication-title: Inf. Sci. – volume: 9 start-page: 303 year: 2005 end-page: 317 ident: bib26 article-title: Evolutionary optimization in uncertain environments-a survey publication-title: IEEE Trans. Evol. Comput. – start-page: 1201 year: 2006 end-page: 1208 ident: bib37 article-title: Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach publication-title: Proceedings of the 8th Conference on Genetic and Evolutionary Computation – start-page: 105 year: 2010 end-page: 123 ident: bib12 article-title: Dynamic multi-objective optimisation using PSO publication-title: Multi-Objective Swarm Intelligent Systems – volume: 61 start-page: 806 year: 2017 end-page: 818 ident: bib13 article-title: A prediction strategy based on center points and knee points for evolutionary dynamic multi-objective optimization publication-title: Appl. Soft Comput. – start-page: 803 year: 2007 end-page: 817 ident: bib16 article-title: Dynamic multi-objective optimization and decision-making using modified NSGA-II: a case study on hydro-thermal power scheduling publication-title: International Conference on Evolutionary Multi-Criterion Optimization – volume: 24 start-page: 66 year: 2013 end-page: 75 ident: bib38 article-title: Dynamic multiobjective optimization using evolutionary algorithm with Kalman filter publication-title: Procedia Comput. Sci. – volume: 15 start-page: 1891 year: 2018 end-page: 1903 ident: bib4 article-title: Robust dynamic multi-objective vehicle routing optimization method publication-title: IEEE ACM Trans. Comput. Biol. Bioinform – volume: 22 start-page: 157 year: 2018 end-page: 171 ident: bib25 article-title: Dynamic multiobjectives optimization with a changing number of objectives publication-title: IEEE Trans. Evol. Comput. – volume: 11 start-page: 41 year: 2016 end-page: 53 ident: bib39 article-title: Ensemble classification and regression-recent developments, applications and future directions publication-title: IEEE Comput. Intell. Mag. – volume: 14 start-page: 31 year: 2014 end-page: 47 ident: bib8 article-title: Population-based metaheuristics for continuous boundary-constrained dynamic multi-objective optimisation problems publication-title: Swarm Evol. Comput. – volume: 2 start-page: 87 year: 2010 end-page: 110 ident: bib28 article-title: A predictive gradient strategy for multiobjective evolutionary algorithms in a fast changing environment publication-title: Memetic Comput. – start-page: 1528 year: 2014 end-page: 1535 ident: bib33 article-title: Find robust solutions over time by two-layer multi-objective optimization method publication-title: IEEE Congress on Evolutionary Computation – volume: 11 start-page: 712 year: 2007 end-page: 731 ident: bib48 article-title: MOEA/D: a multiobjective evolutionary algorithm based on decomposition publication-title: IEEE Trans. Evol. Comput. – volume: 44 start-page: 247 year: 2019 end-page: 259 ident: bib20 article-title: A dynamic multiobjective evolutionary algorithm based on a dynamic evolutionary environment model publication-title: Swarm Evol. Comput. – volume: 13 start-page: 284 year: 2009 end-page: 302 ident: bib49 article-title: Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II publication-title: IEEE Trans. Evol. Comput. – volume: 8 start-page: 425 year: 2004 end-page: 442 ident: bib11 article-title: Dynamic multiobjective optimization problems: test cases, approximations, and applications publication-title: IEEE Trans. Evol. Comput. – volume: 7 start-page: 376 year: 2017 March 23 end-page: 386 ident: bib53 article-title: A PSO-based multi-objective multilabel feature selection method in classification publication-title: Sci. Rep. – start-page: 1 year: 2010 end-page: 6 ident: bib32 article-title: Robust optimization over time a new perspective on dynamic optimization problems publication-title: IEEE Congress on Evolutionary Computation – volume: 13 start-page: 103 year: 2009 end-page: 127 ident: bib23 article-title: A competitive-cooperative coevolutionary paradigm for dynamic multiobjective optimization publication-title: IEEE Trans. Evol. Comput. – volume: 19 start-page: 3221 year: 2015 end-page: 3235 ident: bib30 article-title: A directed search strategy for evolutionary dynamic multiobjective optimization publication-title: Soft Comput. – start-page: 33 year: 2013 end-page: 40 ident: bib19 article-title: Crowding-based local differential evolution with speciation-based memory archive for dynamic multimodal optimization publication-title: Proceedings of the 15th Conference on Genetic and Evolutionary Computation – start-page: 1 year: 2017 end-page: 14 ident: bib40 article-title: Improving metaheuristic algorithms with information feedback models publication-title: IEEE Trans. Cybern. – volume: 30 start-page: 709 year: 2018 end-page: 722 ident: bib10 article-title: Interval multi-objective quantum-inspired cultural algorithms publication-title: Neural Comput. Appl. – volume: 8 start-page: 256 year: 2004 end-page: 279 ident: bib45 article-title: Handling multiple objectives with particle swarm optimization publication-title: IEEE Trans. Evol. Comput. – volume: 5 start-page: 3 year: 2013 end-page: 18 ident: bib34 article-title: A framework for finding robust optimal solutions over time publication-title: Memetic Comput. – volume: 44 start-page: 40 year: 2014 end-page: 53 ident: bib29 article-title: A population prediction strategy for evolutionary dynamic multiobjective optimization publication-title: IEEE Trans. Cybern. – year: 2005 ident: bib43 article-title: Statistical Forecasting and Decision-Making – start-page: 85 year: 2013 end-page: 106 ident: bib22 article-title: Dynamic multi-objective optimization: a survey of the state-of-the-art publication-title: Evolutionary Computation for Dynamic Optimization Problems – year: 2009 ident: bib50 article-title: Evolutionary Multi-Objective Optimization in Uncertain Environments - Issues and Algorithms – volume: 18 start-page: 577 year: 2014 end-page: 601 ident: bib47 article-title: An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: solving problems with box constraints publication-title: IEEE Trans. Evol. Comput. – volume: 16 start-page: 769 year: 2012 end-page: 786 ident: bib7 article-title: Continuous dynamic constrained optimizationThe challenges publication-title: IEEE Trans. Evol. Comput. – volume: 47 start-page: 4223 year: 2017 end-page: 4234 ident: bib24 article-title: Solving multiobjective optimization problems in unknown dynamic environments: an inverse modeling approach publication-title: IEEE Trans. Cybern. – volume: 33 start-page: 1 year: 2017 end-page: 17 ident: bib3 article-title: A survey of swarm intelligence for dynamic optimization: algorithms and applications publication-title: Swarm Evol. Comput. – start-page: 1 year: 2018 end-page: 16 ident: bib9 article-title: Firework-based software project scheduling method considering the learning and forgetting effect publication-title: Soft Comput. – volume: 58 start-page: 631 year: 2017 end-page: 647 ident: bib15 article-title: The effect of diversity maintenance on prediction in dynamic multi-objective optimization publication-title: Appl. Soft Comput. – volume: 261 start-page: 1028 year: 2017 end-page: 1051 ident: bib14 article-title: A coevolutionary technique based on multi-swarm particle swarm optimization for dynamic multi-objective optimization publication-title: Eur. J. Oper. Res. – volume: 7 start-page: 117 year: 2003 end-page: 132 ident: bib52 article-title: Performance assessment of multiobjective optimizers: an analysis and review publication-title: IEEE Trans. Evol. Comput. – volume: 33 start-page: 1 year: 2017 end-page: 17 ident: bib21 article-title: A survey of swarm intelligence for dynamic optimization: algorithms and applications publication-title: Swarm Evol. Comput. – volume: 43 start-page: 2014 year: 2017 end-page: 2032 ident: bib44 article-title: A novel dynamic multi-objective robust evolutionary optimization method publication-title: Acta Autom. Sin. – volume: 2015 start-page: 1 year: 2015 end-page: 18 ident: bib36 article-title: The evolutionary algorithm to find robust Pareto-optimal solutions over time publication-title: Math. Probl Eng. – volume: 15 start-page: 1877 year: 2018 end-page: 1890 ident: bib6 article-title: Environment sensitivity-based cooperative co-evolutionary algorithms for dynamic multi-objective optimization publication-title: IEEE ACM Trans. Comput. Biol. Bioinform – start-page: 103 year: 2001 ident: bib46 article-title: SPEA2: Improving the Strength Pareto Evolutionary Algorithm – start-page: 616 year: 2013 end-page: 625 ident: bib35 article-title: Finding robust solutions to dynamic optimization problems publication-title: European Conference on the Applications of Evolutionary Computation – volume: 8 start-page: 959 year: 2008 end-page: 971 ident: bib2 article-title: Multiobjective optimization immune algorithm in dynamic environments and its application to greenhouse control publication-title: Appl. Soft Comput. – volume: 24 start-page: 1571 year: 2013 end-page: 1588 ident: bib27 article-title: Memory enhanced dynamic multi-objective evolutionary algorithm based on decomposition publication-title: Ruan Jian Xue Bao/J. Software – start-page: 803 year: 2007 ident: 10.1016/j.swevo.2019.03.015_bib16 article-title: Dynamic multi-objective optimization and decision-making using modified NSGA-II: a case study on hydro-thermal power scheduling – volume: 8 start-page: 959 issue: 2 year: 2008 ident: 10.1016/j.swevo.2019.03.015_bib2 article-title: Multiobjective optimization immune algorithm in dynamic environments and its application to greenhouse control publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2007.07.005 – volume: 7 start-page: 117 issue: 2 year: 2003 ident: 10.1016/j.swevo.2019.03.015_bib52 article-title: Performance assessment of multiobjective optimizers: an analysis and review publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2003.810758 – start-page: 1 year: 2010 ident: 10.1016/j.swevo.2019.03.015_bib32 article-title: Robust optimization over time a new perspective on dynamic optimization problems – volume: 13 start-page: 284 issue: 2 year: 2009 ident: 10.1016/j.swevo.2019.03.015_bib49 article-title: Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2008.925798 – volume: 18 start-page: 577 issue: 4 year: 2014 ident: 10.1016/j.swevo.2019.03.015_bib47 article-title: An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: solving problems with box constraints publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2013.2281535 – volume: 33 start-page: 1 year: 2017 ident: 10.1016/j.swevo.2019.03.015_bib21 article-title: A survey of swarm intelligence for dynamic optimization: algorithms and applications publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2016.12.005 – volume: 13 start-page: 103 issue: 1 year: 2009 ident: 10.1016/j.swevo.2019.03.015_bib23 article-title: A competitive-cooperative coevolutionary paradigm for dynamic multiobjective optimization publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2008.920671 – volume: 9 start-page: 303 issue: 3 year: 2005 ident: 10.1016/j.swevo.2019.03.015_bib26 article-title: Evolutionary optimization in uncertain environments-a survey publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2005.846356 – year: 2005 ident: 10.1016/j.swevo.2019.03.015_bib43 – volume: 274 start-page: 17 year: 2014 ident: 10.1016/j.swevo.2019.03.015_bib41 article-title: Chaotic krill herd algorithm publication-title: Inf. Sci. doi: 10.1016/j.ins.2014.02.123 – volume: 6 start-page: 1 year: 2012 ident: 10.1016/j.swevo.2019.03.015_bib1 article-title: Evolutionary dynamic optimization: a survey of the state of the art publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2012.05.001 – volume: 11 start-page: 712 issue: 6 year: 2007 ident: 10.1016/j.swevo.2019.03.015_bib48 article-title: MOEA/D: a multiobjective evolutionary algorithm based on decomposition publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2007.892759 – volume: 5 start-page: 3 issue: 1 year: 2013 ident: 10.1016/j.swevo.2019.03.015_bib34 article-title: A framework for finding robust optimal solutions over time publication-title: Memetic Comput. doi: 10.1007/s12293-012-0090-2 – volume: 15 start-page: 1877 issue: 6 year: 2018 ident: 10.1016/j.swevo.2019.03.015_bib6 article-title: Environment sensitivity-based cooperative co-evolutionary algorithms for dynamic multi-objective optimization publication-title: IEEE ACM Trans. Comput. Biol. Bioinform doi: 10.1109/TCBB.2017.2652453 – start-page: 85 year: 2013 ident: 10.1016/j.swevo.2019.03.015_bib22 article-title: Dynamic multi-objective optimization: a survey of the state-of-the-art – volume: 22 start-page: 157 issue: 1 year: 2018 ident: 10.1016/j.swevo.2019.03.015_bib25 article-title: Dynamic multiobjectives optimization with a changing number of objectives publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2017.2669638 – volume: 47 start-page: 4223 issue: 12 year: 2017 ident: 10.1016/j.swevo.2019.03.015_bib24 article-title: Solving multiobjective optimization problems in unknown dynamic environments: an inverse modeling approach publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2016.2602561 – volume: 2015 start-page: 1 issue: 6 year: 2015 ident: 10.1016/j.swevo.2019.03.015_bib36 article-title: The evolutionary algorithm to find robust Pareto-optimal solutions over time publication-title: Math. Probl Eng. – start-page: 103 year: 2001 ident: 10.1016/j.swevo.2019.03.015_bib46 – volume: 2 start-page: 87 issue: 2 year: 2010 ident: 10.1016/j.swevo.2019.03.015_bib28 article-title: A predictive gradient strategy for multiobjective evolutionary algorithms in a fast changing environment publication-title: Memetic Comput. doi: 10.1007/s12293-009-0026-7 – volume: 7 start-page: 376 year: 2017 ident: 10.1016/j.swevo.2019.03.015_bib53 article-title: A PSO-based multi-objective multilabel feature selection method in classification publication-title: Sci. Rep. doi: 10.1038/s41598-017-00416-0 – volume: 16 start-page: 769 issue: 6 year: 2012 ident: 10.1016/j.swevo.2019.03.015_bib7 article-title: Continuous dynamic constrained optimizationThe challenges publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2011.2180533 – volume: 44 start-page: 40 issue: 1 year: 2014 ident: 10.1016/j.swevo.2019.03.015_bib29 article-title: A population prediction strategy for evolutionary dynamic multiobjective optimization publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2013.2245892 – volume: 24 start-page: 66 year: 2013 ident: 10.1016/j.swevo.2019.03.015_bib38 article-title: Dynamic multiobjective optimization using evolutionary algorithm with Kalman filter publication-title: Procedia Comput. Sci. doi: 10.1016/j.procs.2013.10.028 – start-page: 105 year: 2010 ident: 10.1016/j.swevo.2019.03.015_bib12 article-title: Dynamic multi-objective optimisation using PSO – volume: 14 start-page: 31 year: 2014 ident: 10.1016/j.swevo.2019.03.015_bib8 article-title: Population-based metaheuristics for continuous boundary-constrained dynamic multi-objective optimisation problems publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2013.08.004 – volume: 6 start-page: 1 year: 2012 ident: 10.1016/j.swevo.2019.03.015_bib18 article-title: Evolutionary dynamic optimization: a survey of the state of the art publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2012.05.001 – start-page: 616 year: 2013 ident: 10.1016/j.swevo.2019.03.015_bib35 article-title: Finding robust solutions to dynamic optimization problems – volume: 15 start-page: 1891 issue: 6 year: 2018 ident: 10.1016/j.swevo.2019.03.015_bib4 article-title: Robust dynamic multi-objective vehicle routing optimization method publication-title: IEEE ACM Trans. Comput. Biol. Bioinform doi: 10.1109/TCBB.2017.2685320 – volume: 261 start-page: 1028 issue: 3 year: 2017 ident: 10.1016/j.swevo.2019.03.015_bib14 article-title: A coevolutionary technique based on multi-swarm particle swarm optimization for dynamic multi-objective optimization publication-title: Eur. J. Oper. Res. doi: 10.1016/j.ejor.2017.03.048 – volume: 30 start-page: 709 issue: 3 year: 2018 ident: 10.1016/j.swevo.2019.03.015_bib10 article-title: Interval multi-objective quantum-inspired cultural algorithms publication-title: Neural Comput. Appl. doi: 10.1007/s00521-016-2572-5 – volume: 61 start-page: 806 year: 2017 ident: 10.1016/j.swevo.2019.03.015_bib13 article-title: A prediction strategy based on center points and knee points for evolutionary dynamic multi-objective optimization publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2017.08.004 – start-page: 33 year: 2013 ident: 10.1016/j.swevo.2019.03.015_bib19 article-title: Crowding-based local differential evolution with speciation-based memory archive for dynamic multimodal optimization – start-page: 1 issue: 99 year: 2017 ident: 10.1016/j.swevo.2019.03.015_bib40 article-title: Improving metaheuristic algorithms with information feedback models publication-title: IEEE Trans. Cybern. – start-page: 3192 year: 2014 ident: 10.1016/j.swevo.2019.03.015_bib51 article-title: Evolutionary multiobjective optimization in dynamic environments: a set of novel benchmark functions – start-page: 1 year: 2018 ident: 10.1016/j.swevo.2019.03.015_bib9 article-title: Firework-based software project scheduling method considering the learning and forgetting effect publication-title: Soft Comput. – start-page: 1201 year: 2006 ident: 10.1016/j.swevo.2019.03.015_bib37 article-title: Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach – volume: 394 start-page: 183 year: 2017 ident: 10.1016/j.swevo.2019.03.015_bib31 article-title: A multi-objective approach to robust optimization over time considering switching cost publication-title: Inf. Sci. doi: 10.1016/j.ins.2017.02.029 – volume: 11 start-page: 41 issue: 1 year: 2016 ident: 10.1016/j.swevo.2019.03.015_bib39 article-title: Ensemble classification and regression-recent developments, applications and future directions publication-title: IEEE Comput. Intell. Mag. doi: 10.1109/MCI.2015.2471235 – volume: 8 start-page: 425 issue: 5 year: 2004 ident: 10.1016/j.swevo.2019.03.015_bib11 article-title: Dynamic multiobjective optimization problems: test cases, approximations, and applications publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2004.831456 – start-page: 629 year: 2015 ident: 10.1016/j.swevo.2019.03.015_bib5 article-title: Evolutionary computation for dynamic optimization problems – volume: 33 start-page: 1 year: 2017 ident: 10.1016/j.swevo.2019.03.015_bib3 article-title: A survey of swarm intelligence for dynamic optimization: algorithms and applications publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2016.12.005 – volume: 44 start-page: 247 year: 2019 ident: 10.1016/j.swevo.2019.03.015_bib20 article-title: A dynamic multiobjective evolutionary algorithm based on a dynamic evolutionary environment model publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2018.03.010 – volume: 44 start-page: 2221 issue: 11 year: 2014 ident: 10.1016/j.swevo.2019.03.015_bib17 article-title: Active robust optimization: enhancing robustness to uncertain environments publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2014.2304475 – volume: 24 start-page: 1571 issue: 7 year: 2013 ident: 10.1016/j.swevo.2019.03.015_bib27 article-title: Memory enhanced dynamic multi-objective evolutionary algorithm based on decomposition publication-title: Ruan Jian Xue Bao/J. Software – volume: 58 start-page: 631 year: 2017 ident: 10.1016/j.swevo.2019.03.015_bib15 article-title: The effect of diversity maintenance on prediction in dynamic multi-objective optimization publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2017.05.008 – volume: 8 start-page: 256 issue: 3 year: 2004 ident: 10.1016/j.swevo.2019.03.015_bib45 article-title: Handling multiple objectives with particle swarm optimization publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2004.826067 – volume: 19 start-page: 3221 issue: 11 year: 2015 ident: 10.1016/j.swevo.2019.03.015_bib30 article-title: A directed search strategy for evolutionary dynamic multiobjective optimization publication-title: Soft Comput. doi: 10.1007/s00500-014-1477-4 – year: 1994 ident: 10.1016/j.swevo.2019.03.015_bib42 – volume: 43 start-page: 2014 issue: 11 year: 2017 ident: 10.1016/j.swevo.2019.03.015_bib44 article-title: A novel dynamic multi-objective robust evolutionary optimization method publication-title: Acta Autom. Sin. – start-page: 1528 year: 2014 ident: 10.1016/j.swevo.2019.03.015_bib33 article-title: Find robust solutions over time by two-layer multi-objective optimization method – year: 2009 ident: 10.1016/j.swevo.2019.03.015_bib50 |
| SSID | ssj0000602559 |
| Score | 2.4983656 |
| Snippet | Many real-world multi-objective optimization problems are subject to environmental changes over time, resulting in changing Pareto-optima. Wide studies on... |
| SourceID | crossref elsevier |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 156 |
| SubjectTerms | Dynamic multi-objective optimization problem Ensemble prediction Evolutionary algorithm Robust Pareto-optimum over time |
| Title | Ensemble prediction-based dynamic robust multi-objective optimization methods |
| URI | https://dx.doi.org/10.1016/j.swevo.2019.03.015 |
| Volume | 48 |
| WOSCitedRecordID | wos000473374800011&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 issn: 2210-6502 databaseCode: AIEXJ dateStart: 20110301 customDbUrl: isFulltext: true dateEnd: 99991231 titleUrlDefault: https://www.sciencedirect.com omitProxy: false ssIdentifier: ssj0000602559 providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3Pb9MwFLbQxoELgwFigyEfdiue8sOJ7eM0dQzEJqQNqTtFduwiqi2tknbbn897sdNlLZoAiUtUWXXd2J-ePz-_9z5C9oEDGKETzoyzjsEOnTMJtJVJJzjwZdiSbKta8lWcncnRSH0LN_hNKycgqkre3anZf11qaIPFxtTZv1ju5Y9CA3yGRYcnLDs8_2jhh1XjrjEfalbjJQwOxHCvsgPr1ecH9dQsmrmPJWRTM_E2bzAF63Ed0jKDsnTT567nt7r2ghruJrwBhtyVrS7Egwv9T4vWAXuJUTZLsxIc0yeL-7ajkBpy6jDZ7ke_2ccJd9gNbgnMhJJ9t8R6vgyatAQOmAw44QP76yttBgMaZ3lvL469PMuamfceh8lBcwsvjPF5vlKtTwxdqZ99joPimDGWOhOoSL2ZiEyBCdw8_DwcfVm65KK8PWChHGH3P7s6VW1E4Npov-cyPX5y8YI8DwcLeugB8ZI8cdU22epEO2iw4a_IaYcPuooPGvBBPT7oCj5oHx804OM1-X48vDg6YUFTg5VAVuZM2ywzWNPPxVJxPY5FyU0qy0QC9XcmjU02jjScuCKtDNA5YXMLlFrn1hiu7Th9QzaqaeXeEppxA-zaRZorznWaqtKIsbS5tk7FJlc7JOlmpyhDwXnUPbkqusjCSdFOaYFTWkRpAVO6Qz4uO818vZXHv553014EyuipYAFQeazj7r92fEee3cP9PdmY1wu3R56WN_OfTf0hQOoXEPKUvQ |
| linkProvider | Elsevier |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Ensemble+prediction-based+dynamic+robust+multi-objective+optimization+methods&rft.jtitle=Swarm+and+evolutionary+computation&rft.au=Guo%2C+Yinan&rft.au=Yang%2C+Huan&rft.au=Chen%2C+Meirong&rft.au=Cheng%2C+Jian&rft.date=2019-08-01&rft.pub=Elsevier+B.V&rft.issn=2210-6502&rft.volume=48&rft.spage=156&rft.epage=171&rft_id=info:doi/10.1016%2Fj.swevo.2019.03.015&rft.externalDocID=S2210650218302712 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2210-6502&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2210-6502&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2210-6502&client=summon |